{"id":1425,"date":"2026-05-24T15:29:31","date_gmt":"2026-05-24T15:29:31","guid":{"rendered":"https:\/\/lean-app.com\/?p=1425"},"modified":"2026-09-08T18:18:27","modified_gmt":"2026-09-08T18:18:27","slug":"lean-vs-noom","status":"publish","type":"post","link":"https:\/\/lean-app.com\/en\/lean-vs-noom\/","title":{"rendered":"Lean vs Noom: psychological coaching vs metabolic precision"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" fetchpriority=\"low\">\n<link 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18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1425 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1425 #lvm-shell .wrap,\nbody.postid-1425 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1425 #lvm-shell .wrap,\n  body.postid-1425 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1425 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1425 #lvm-shell *{max-width:100%}\nbody.postid-1425 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1425 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1425 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1425 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE (badges plus gros + centrage) === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1425 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1425 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1425 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1425 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1425 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1425 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1425 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1425 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7: redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1425 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1425 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1425 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1425 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  \/* v13: charts FULL WIDTH (less card padding) + plus hauts pour vraie respiration *\/\n  body.postid-1425 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1425 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1425 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1425 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1425 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1425 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/MFP === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1425 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1425 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#F5F5F7!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"NOOM\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF6E5E!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1425 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS partie 7 (triplet NEAT\/EAT\/TEF) === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1425 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1425 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1425 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1425 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1425 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1425 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1425 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1425 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR (override mobile mini-phone) === *\/\nbody.postid-1425 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n\n\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/en\/\" aria-label=\"Lean home\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n      <span>Lean<\/span>\n    <\/a>\n    <span class=\"nav-spacer\"><\/span>\n    <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">TDEE calculator<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download on the App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Available on Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/en\/\">Home<\/a> &nbsp;\/&nbsp; Lean vs Noom<\/div>\n  <div class=\"eyebrow\">Comparison &middot; Nutrition &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean versus Noom.\n    <span class=\"alt\">Psychological coaching versus metabolic precision.<\/span>\n  <\/h1>\n  <p class=\"dek\">Noom sells behavioral coaching to change your habits. Lean sees your real expenditure. Two promises that don&rsquo;t play on the same field.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>The Lean Team<\/strong> &middot; 12&nbsp;min read &middot; Updated May 24, 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Free download<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Noom is known for its long, personalized sign-up quiz, its daily food-psychology lessons, its green\/yellow\/red food classification, and access to a human coach. A real strength for adherence and habit work. But its TDEE formula remains Mifflin-St Jeor 1990, plus a static activity factor you tick once during the sign-up quiz. No real bodyfat measured inside the app, no metabolic adaptation. Over 3 months of a serious cut, the gap widens.\n    <\/div>\n    <div class=\"phone-wrap rev\">\n      <div class=\"phone-stage\">\n        <div class=\"tap-hint mobile\" id=\"tapHintMobile\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interactive demo<\/small>Tap the screen to explore the app<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interactive demo<\/small>Tap the screen<br>to explore the app<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 104 34\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M4 9 C 34 1, 64 20, 94 27\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\"\/>\n            <path d=\"M86 20 L 94 27 L 84 30\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"phone\" id=\"phone\" role=\"img\" aria-label=\"Preview of the Lean app with TDEE drill-down\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Back\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Lean preview, Expenditure tab\"><\/div>\n            <div class=\"phone-zones\" id=\"phoneZones\">\n              <div class=\"z\" data-sub=\"BMR\"  style=\"top:11%;height:21%\" role=\"button\" tabindex=\"0\" aria-label=\"BMR detail\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"NEAT detail\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"EAT detail\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"TEF detail\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Balance tab\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Calories tab\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Expenditure tab\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Strategy tab\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Navigate the Lean app\">\n          <button data-tab=\"bilan\"     type=\"button\">Balance<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calories<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Expenditure<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategy<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Quick answer<\/div>\n    <p>Noom calculates your TDEE with Mifflin-St Jeor 1990 (no bodyfat measured inside the app) and a static activity factor chosen during the sign-up quiz. Noom&rsquo;s real strength is elsewhere: a personalized quiz that creates strong initial engagement, daily food-psychology lessons, a green\/yellow\/red food classification, and access to a human coach who works on adherence. Lean takes a different stance: recalculate every component of TDEE (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energy expended at rest. In Lean, calculated on actual lean mass via BodyScan AI.<\/span><\/span> on real bodyfat via a patented proprietary model, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Expenditure from steps and daily activities outside of sport.<\/span><\/span> from steps, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Expenditure tied to sport sessions, calculated through MET.<\/span><\/span> via MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energy spent on digestion. Depends on the macros you eat.<\/span><\/span> per macros) and modulate the BMR through metabolic adaptation continuously, with no coefficient to pick.<\/p>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"constat\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">00 &middot; The reality<\/span><\/div>\n  <h2 id=\"constat\">Noom sells coaching, not your metabolic adaptation<\/h2>\n  <p>If you&rsquo;re reading this, you&rsquo;ve probably already installed Noom. You took the long sign-up quiz, those 20 minutes of very personal questions about your history with weight, your blocks, your emotions, your habits. You felt understood. You entered your weight, your height, your age, your sex, and picked your activity level from a static list. The app showed you a calorie target, say 1,500&nbsp;kcal to lose weight.<\/p>\n  <p>You followed the daily 5 to 10 minute lessons on food psychology. You classified your meals as green, yellow, red. You chatted with your human coach on tough days. For the first 6 weeks, it works. You lose. You&rsquo;re happy. Then around week 8, the scale freezes. You tighten the screws. You drop to 1,350&nbsp;kcal. Still nothing moves.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 to &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">of measured TDEE decline after 4 to 6 weeks of a &minus;500&nbsp;kcal\/day deficit. Noom doesn&rsquo;t detect it. Your calorie target stays frozen on the activity factor you ticked during the sign-up quiz, 100&nbsp;days ago.<\/div>\n  <\/div>\n\n  <p>Imagine Noom shows you a TDEE of 2,000&nbsp;kcal. You eat 1,500 (theoretical deficit of 500&nbsp;kcal). But in reality, your <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/depense-energetique-totale-v2\/\">TDEE has dropped to 1,700&nbsp;kcal<\/a> due to metabolic adaptation. You&rsquo;re only at a 200&nbsp;kcal real deficit, not 500. Loss slows drastically. No daily Noom lesson can fix that, because the problem isn&rsquo;t in your head, it&rsquo;s in the equation.<\/p>\n  <p>The Noom promise is clear and delivered on its behavioral side: you feel supported, you work on your emotional triggers, you learn to classify the quality of your choices. It&rsquo;s valuable for adherence. What Noom doesn&rsquo;t do is <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">recompute your expenditure<\/a> as weeks of deficit go by. And that's exactly where the \"calorie tracker\" promise stops, even though it's the lever that actually drives weight loss.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01 &middot; Problem 1<\/span><\/div>\n  <h2 id=\"p1\">The 1990 BMR formula, with no bodyfat measured in the app<\/h2>\n  <p>Behind the daily lessons and the food color system, Noom still has to set a number: your basal metabolic rate, the energy burned at rest. It gets it with the Mifflin-St Jeor equation, the one used by the overwhelming majority of consumer trackers.<\/p>\n  <p>Mifflin-St Jeor dates from 1990. On paper it is progress: 498 subjects, indirect calorimetry, a more representative population than the 1919 work. Noom applies it as is, with no variant.<\/p>\n  <p>Some competitors at least offer a way out, the Katch-McArdle equation, which works on lean mass if you enter your body fat percentage. Noom does not offer that option: no body fat field, no alternative calculation. The coaching therefore rests on an estimate that nothing ever corrects.<\/p>\n  <p>The progress from 1919 to 1990 is real but marginal, because the underlying flaw does not move: the equation only knows your weight. Neither your body fat nor your lean mass.<\/p>\n  <p>Yet fat mass burns very little energy at rest. Organs and muscles do the spending: liver, brain, heart, kidneys. Two bodies of the same weight with different compositions therefore do not have the same metabolism.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) tested Mifflin-St Jeor against reference indirect calorimetry: 87% accuracy in non-obese subjects, but only 68% in obese subjects, with errors reaching 330 kcal per day.<\/p>\n\n  <p style=\"margin-bottom:8px\"><strong>Worked example.<\/strong> Woman at 1.65m, 85&nbsp;kg, 38&nbsp;% bodyfat&nbsp;:<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 1<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartBMR\" aria-label=\"BMR comparison: Mifflin-St Jeor 1670 kcal vs Lean patented proprietary model 1340 kcal, 330 kcal gap\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Estimated BMR<\/strong> for a woman at 1.65m, 85&nbsp;kg, 38&nbsp;% bodyfat. The patented proprietary Lean model accounts for lean mass. Mifflin-St Jeor (Noom by default, with no lean-mass option), doesn&rsquo;t. A 330&nbsp;kcal gap, the equivalent of a full light meal.<\/p>\n  <\/div>\n\n  <p>A 330 kcal error is the difference between a deficit that works and an unexplained plateau. No behavioral support, however good, makes up for a calorie target that is wrong from the start: it will simply make you more diligent on the wrong target.<\/p>\n\n  <div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:200px\">\n    <div class=\"mini-phone\" style=\"max-width:200px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"BodyScan IA Lean : bodyfat mesur\u00e9 par photo en 5 secondes\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n    <div class=\"mini-cap\">Real body fat<strong>Photo, 5 seconds<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400 kcal<\/div>\n    <div class=\"lbl\">gap between two women at 75&nbsp;kg, one at 22&nbsp;% bodyfat (BMR 1,650), the other at 38&nbsp;% (BMR 1,250). Noom gives them the same number, with no lean-mass option.<\/div>\n  <\/div>\n\n  <p>The conclusion is arithmetic: an app that only knows your weight, height, age and sex cannot individualize your metabolism. It lacks the variable that matters.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p2\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">02 &middot; Problem 2<\/span><\/div>\n  <h2 id=\"p2\">The activity factor, picked once and for all<\/h2>\n  <p>That is the link coaching cannot compensate for.<\/p>\n  <p>Once the basal metabolic rate is estimated, Noom has to derive your total expenditure from it: BMR plus steps, daily activities, workouts and digestion.<\/p>\n  <p>The method fits in one question of the sign-up quiz: pick your activity level from a list. That coefficient is called PAL, for Physical Activity Level.<\/p>\n  <ul>\n    <li>Sedentary (PAL 1.25): desk job, little walking<\/li>\n    <li>Lightly active (PAL 1.4): occasional walking, little sport<\/li>\n    <li>Active (PAL 1.6): regular walking, sport 3 to 5 times per week<\/li>\n    <li>Very active (PAL 1.8): intense sport almost daily or physical work<\/li>\n  <\/ul>\n  <p>The BMR is then multiplied by that number. That is the whole mechanism behind your daily target: a box ticked on day one, never revisited.<\/p>\n  <p>The approximation is crude. Between a Sunday on the couch and a day spent standing and walking, the real gap far exceeds what a single coefficient can represent.<\/p>\n  <p>Noom syncs correctly with Apple Health and Google Fit and collects your steps. A calorie bonus can be added when a workout is detected. But the base of the calculation remains the multiplier chosen at sign-up.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 2 &middot; 7 real days<\/span><span class=\"r\">kcal\/day<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartNEAT\" aria-label=\"Daily variability of caloric expenditure over 7 days, vs 2000 kcal fixed per Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Real expenditure<\/strong> measured over 7&nbsp;days for a Lean user. The grey line is what Noom was showing (2,000&nbsp;kcal flat, PAL Active \u00d7 BMR). The pink annotations show why each day moves.<\/p>\n  <\/div>\n\n  <p>Your activity does not fit in a box. You can be very active the week you chain trips, and sedentary the week you work from home.<\/p>\n  <p>So which box do you tick? None is right, and the displayed TDEE stays durably off from reality.<\/p>\n  <p>This is the central point: even with a modern metabolism equation, a static PAL is enough to distort the whole. NEAT, EAT and TEF cannot be derived from a single multiplier.<\/p>\n  <p>A metabolism estimated without a body composition measurement, plus an activity expenditure approximated by a frozen coefficient: the odds that the final target is right are low.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">See your real TDEE, broken down into BMR + NEAT + EAT + TEF. Free download.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problem 3<\/span><\/div>\n  <h2 id=\"p3\">Metabolic adaptation, never modeled<\/h2>\n  <p>It is the blind spot that neither the daily lessons nor the coaches cover.<\/p>\n  <p>In a prolonged deficit, your body notices it is receiving less energy and reduces its consumption. Like a phone switching to low-power mode: everything keeps running, but slower.<\/p>\n  <p>That is metabolic adaptation, and the literature is consistent: M\u00fcller 2015 (PubMed 26399868, reanalysis of the Minnesota study), Doucet 2001 on prolonged deficit, Nunes 2020 (PMC7484122). Published ranges run from 5 to 25% of basal metabolic rate.<\/p>\n  <ul>\n    <li>Deficit of &minus;250&nbsp;kcal per day, over 2 to 8 weeks: adaptation of <strong>5 to 10%<\/strong> (TDEE drops to 90-95&nbsp;% of the initial level)<\/li>\n    <li>Deficit of &minus;500&nbsp;kcal per day: <strong>10 to 15%<\/strong> adaptation (TDEE drops to 85-90&nbsp;%)<\/li>\n    <li>Deficit of &minus;750&nbsp;kcal per day: <strong>15 to 25%<\/strong> adaptation (TDEE drops to 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Lean convention: 100% means an optimal metabolism, 90% a 10% adaptation. And since NEAT, EAT and TEF are all computed from BMR, the whole TDEE moves.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 3 &middot; 8 weeks in deficit<\/span><span class=\"r\">kcal\/day<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartAdapt\" aria-label=\"TDEE dropping from 2000 to 1720 kcal over 8 weeks, vs 2000 fixed per Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>real TDEE<\/strong> over 8 weeks of deficit at &minus;500&nbsp;kcal\/day. The pink curve drops. The Noom line stays flat. By week 6, you&rsquo;re already at maintenance. Without having changed anything.<\/p>\n  <\/div>\n\n  <p>A worked example: you target a 25% deficit on a 2,000 kcal TDEE, so 1,500 kcal per day. Your body adapts by 14%, your real TDEE drops to 1,720. Only 220 kcal of deficit remain: the loss stops, without you having changed anything.<\/p>\n  <p>What makes the phenomenon formidable is its slowness. The first weeks work, you are confident, you keep going. The adaptation builds up silently until the day the scale freezes.<\/p>\n  <p>That is precisely the moment behavioral support turns against you. The coach will explain that the plateau is normal, that you must persevere, review your habits. Whereas the problem is neither your discipline nor your motivation: it is the target number that moved, and nobody measured it.<\/p>\n  <p>Noom does not model this phenomenon. Your calorie target stays frozen as long as you do not update your weight by hand. You can follow every lesson and color-code every food: if the target is wrong, the method cannot catch you.<\/p>\n<\/section>\n\n<section aria-labelledby=\"solution\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04 &middot; Lean's solution<\/span><\/div>\n  <h2 id=\"solution\">How Lean fixes each of the 3 problems<\/h2>\n  <p>Noom and Lean do not play on the same field. Noom bets on behavioral psychology: daily lessons, human coaches, food color coding. It is consistent, and for some profiles it is exactly what is needed. But behavioral support sitting on a wrong calorie target remains support toward the wrong target. Lean works on the other half of the problem: making that number right, by measuring every component of TDEE (BMR + NEAT + EAT + TEF) plus metabolic adaptation. Here is how.<\/p>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"duo-row\">\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9 par photo\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Step 1<strong>AI BodyScan<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp\" alt=\"\u00c9cran BMR Lean : m\u00e9tabolisme de base calcul\u00e9 sur la masse maigre\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Step 2<strong>BMR recalculated<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">BMR on real bodyfat<\/div>\n      <h3>Proprietary patented model, built on lean mass<\/h3>\n      <p>Noom's coaching starts from a calorie target computed on your weight. Lean starts from your <strong>lean mass<\/strong>, because that is what burns at rest: at identical weight, two people do not have the same metabolism. You still need to know your body fat percentage without going through a clinical DEXA scan.<\/p>\n      <p>Hence the <strong>AI BodyScan<\/strong>&nbsp;: one photo, analyzed by a model trained on a bank of DEXA scans, and your body fat appears in a few seconds. Repeated every week, it updates your metabolism automatically. No human coach can produce this measurement at this frequency.<\/p>\n      <p>Gone are the skinfold calipers, the impedance scale and its swings with hydration, the DEXA scan and its price. One photo a week is enough.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">No activity coefficient<\/div>\n      <h3>NEAT, EAT, TEF calculated separately<\/h3>\n      <p><strong>NEAT.<\/strong> Your real steps arrive via HealthKit (iOS) or Google Fit (Android). Where a coaching program asks you to describe your activity level, Lean reads your phone's accelerometers and converts those steps into calories according to your metabolism. The difference between a 4,000-step day and a 14,000-step day shows immediately in your target for the day.<\/p>\n      <p><strong>EAT.<\/strong> You pick your sport and Lean applies the matching MET to your actual effort time. An hour of lifting with its rest periods does not cost an hour of continuous running: counting them the same distorts the balance by several hundred kcal per week.<\/p>\n      <p><strong>TEF.<\/strong> Digestion burns energy, and not at the same rate for each macro: 20 to 30% for protein, 5 to 10% for carbohydrates, 1 to 3% for fat. Lean computes this item on what you actually ate, instead of the flat 10% applied everywhere else.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"mini-phone\" style=\"max-width:170px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method<strong>Auto adaptation<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">Automatic metabolic adaptation<\/div>\n      <h3>A world first on a consumer app<\/h3>\n      <p><strong>Metabolic adaptation.<\/strong> It is the blind spot of every behavioral program: after a few weeks of deficit, your metabolism slows down, and no motivation makes up for a calorie target that has become wrong. Lean adjusts your TDEE downward according to the published ranges (M\u00fcller 2015, Doucet 2001), week after week.<\/p>\n      <p>Beyond 10 to 15% adaptation, the app may recommend a return to maintenance to restart the metabolism before going again. That is what a coach does, except Lean computes it on your data.<\/p>\n      <p>No activity level to declare, no box ticked once and for all. Every brick is measured, every week.<\/p>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Side-by-side<\/span><\/div>\n  <h2 id=\"tab\">Lean versus Noom, criterion by criterion<\/h2>\n  <p>An honest read of each app's strengths and weaknesses. No criterion touches price.<\/p>\n\n  <div class=\"table\" role=\"table\" aria-label=\"Lean vs Noom comparison\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Criterion<\/div>\n      <div class=\"brand-cell lean\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Lean<\/span><\/div>\n      <div class=\"brand-cell\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Noom<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">BMR formula<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Proprietary patented model (lean mass)<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Mifflin-St Jeor 1990, no lean-mass option<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Uses bodyfat<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes, measured in the app<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, no bodyfat input possible<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Bodyfat measured inside the app<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> BodyScan AI via photo<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (steps, non-exercise activity)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Computed from real steps every day<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> HealthKit sync, exercise calorie add-on, but outside any TDEE recomputation<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (exercise expenditure)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Per sport via MET, effective time<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Simple sport selection, standard exercise database<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digestion)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Calculated from macros, integrated into the TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, macros displayed without TEF computation<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Metabolic adaptation<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Automatic, week by week<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Activity multiplier to pick<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> No, computed on real data<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Yes, static level chosen through the sign-up quiz<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">AI photo scan of a meal<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes, unlimited<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, manual entry or barcode<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Barcode scan<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Food database<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> USDA + OpenFoodFacts, curated<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Proprietary database + green\/yellow\/red classification<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Calorie deficit recommendation<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Adapted to real TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fixed target, manual recompute required<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Human coaching and behavioral therapy<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Out of scope, focus on TDEE computation<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Human coaches, groups, daily lessons<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Green\/yellow\/red food classification<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Out of scope<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Mainstream educational reference<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EU coverage and localization<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> FR, EN, ES, PT, IT, DE, PL, HU<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> EN, ES, DE and others, founded in NYC 2008<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Reputation and audience size<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4.7\/5, 10,000+ users, young FR app<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4.5\/5, 50M+ downloads, audience women 35-55<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Business model<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Premium, 7-day free trial on the annual subscription<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Paid subscription, short trial period<\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tracking\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">06 &middot; Tracking<\/span><\/div>\n  <h2 id=\"tracking\">3 ways to track a meal<\/h2>\n  <p>A coaching program lasts if the daily gesture is simple. That is exactly Lean's bet on tracking: three ways to log a meal, so that no situation becomes an excuse to quit.<\/p>\n\n  <div class=\"mini-row\">\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-database.webp\" alt=\"Recherche dans la base de donn\u00e9es USDA + OpenFoodFacts\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method 1<strong>Food database<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-codebarre.webp\" alt=\"Scan de code-barres dans Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method 2<strong>Barcode<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-scania.webp\" alt=\"Scan photo IA d'un plat\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method 3<strong>AI photo scan<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>Database search.<\/strong> Curated base, USDA + OpenFoodFacts. No community noise, no \"Roast chicken\" entered 47 times by 47 different users with 47 different values.<\/li>\n    <li><strong>Barcode scan.<\/strong> Standard. You scan your pasta box, you get the macros.<\/li>\n    <li><strong>AI photo scan of a meal.<\/strong> You take a photo of your plate, the AI detects the foods, you get calories and macros per food. Noom doesn&rsquo;t offer this feature.<\/li>\n  <\/ol>\n  <p>AI photo scanning is most useful when you eat out. Noom will ask you to qualify your dish by color; Lean asks you for a photo, and you move on. At a business lunch or a dinner with friends, the difference in friction is decisive.<\/p>\n  <p>Above the meal, Lean shows a TDEE that moves during the day: the more you walk, the higher your calorie target goes. A fixed weekly program cannot render that daily variation.<\/p>\n  <p>And to rank what really matters, the Progression Pyramid:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Lean Progression Pyramid\">\n    <div class=\"level l1\"><span>Adherence<\/span><span class=\"k\">Base<\/span><\/div>\n    <div class=\"level l2\"><span>Calorie target<\/span><span class=\"k\">Tier 2<\/span><\/div>\n    <div class=\"level l3\"><span>Steps \/ NEAT<\/span><span class=\"k\">Tier 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrients<\/span><span class=\"k\">Top<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">Don&rsquo;t skip steps. If you&rsquo;re not consistent on tracking, optimizing macros to the percent is pointless.<\/div>\n<\/section>\n\n<section aria-labelledby=\"noom-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honesty<\/span><\/div>\n  <h2 id=\"noom-better\">What Noom does better<\/h2>\n  <p>Lean is not perfect, and Noom has several real strengths worth acknowledging. Honest read, criterion by criterion, on the axes where Noom stays ahead. None of these axes is secondary: they are real pillars of the Noom promise, and they explain its massive adoption among the target audience of women aged 35 to 55 on the long-term weight loss topic.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Noom vs Lean scorecard across 4 axes: psychology and adherence\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Axis<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Noom<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Human coaching and behavioral therapy<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:94%\"><\/i><\/div><div class=\"v\">9,4<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:20%\"><\/i><\/div><div class=\"v\">2,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Daily food-psychology lessons<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:25%\"><\/i><\/div><div class=\"v\">2,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Intuitive green\/yellow\/red classification<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:88%\"><\/i><\/div><div class=\"v\">8,8<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:30%\"><\/i><\/div><div class=\"v\">3,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Long-term adherence work<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:70%\"><\/i><\/div><div class=\"v\">7,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Honest read.<\/strong> On human coaching, Noom is the mainstream reference: your coach chats with you, the support groups (Noom community) run continuously, and it&rsquo;s a real emotional accompaniment for those who need it. On the daily food-psychology lessons (5 to 10 minutes each day, inspired by CBT, cognitive behavioral therapy), Noom has invested massively and it&rsquo;s unique on the market: no other calorie tracker offers this structured educational content. On the green\/yellow\/red classification, it&rsquo;s an intuitive mechanism that saves the user time and works well for profiles who don&rsquo;t want to dive into macros. On long-term adherence, Chin 2016 and many meta-analyses on behavioral therapy applied to weight loss show significant gains at 6 and 12 months. Noom builds scientifically on that axis.<\/p>\n  <p>If your main angle is psychological work on food habits, if you need a human coach to hold on, or if the green\/yellow\/red classification helps you make choices without calculating, Noom is more relevant than Lean. If your angle is the precision of <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">TDEE calculation<\/a>, bodyfat measured every week through BodyScan AI, and automatic metabolic adaptation, that&rsquo;s exactly what was demonstrated in the 3 previous sections. Many users run Lean for measurement and Noom in parallel for psychological coaching, which is entirely defensible.<\/p>\n<\/section>\n\n<section aria-labelledby=\"forwho\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08 &middot; Who it's for<\/span><\/div>\n  <h2 id=\"forwho\">Who Lean is built for<\/h2>\n  <p>Four profiles. If one of them sounds like you, Lean is likely a good fit.<\/p>\n\n  <div class=\"persona\">\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You followed Noom seriously and didn&rsquo;t lose<\/h4>\n        <p>You took the quiz, followed the lessons, color-coded your meals, talked with your coach, and held on for several weeks without the curve really following.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You plateau after several weeks of cutting<\/h4>\n        <p>The plateau settles in after four to eight weeks. That is the signature of metabolic adaptation: Lean computes it and corrects your target instead of sending you back to your motivation.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You want to understand your metabolism<\/h4>\n        <p>You want to see the detail of the calculation: BMR, NEAT, EAT and TEF displayed separately, adaptation explained on its own, rather than a single number commented by a coach.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You want tracking that lasts 12 months<\/h4>\n        <p>You often eat out and you need fast logging: photo, curated database or barcode depending on the context.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Noom stays more relevant for<\/strong>&nbsp;: working psychologically on food habits, enjoying a human coach and support groups, following daily lessons of cognitive behavioral therapy applied to weight loss, or relying on the green\/yellow\/red classification to make choices without calculating. Precision of TDEE calculation and metabolic adaptation just aren&rsquo;t part of its main promise.<\/p>\n<\/section>\n\n<section aria-labelledby=\"migrate\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">09 &middot; Migration<\/span><\/div>\n  <h2 id=\"migrate\">Switching from Noom to Lean (or using both) in 3 minutes<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Download Lean<\/h4><p>App Store or Play Store. Sign-up in thirty seconds, with no twenty-minute quiz.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>AI BodyScan<\/h4><p>One photo, five seconds: your body fat percentage appears.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Weight &amp; height<\/h4><p>You enter your weight and height. Nothing else is asked.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean calculates<\/h4><p>BMR on real lean mass, NEAT from your steps via HealthKit or Google Fit, EAT by MET, TEF on your macros, and metabolic adaptation modulating it all week after week.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Log a meal<\/h4><p>Photo, barcode or database: you choose depending on the meal.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Important note.<\/strong> Lean doesn&rsquo;t import your Noom history automatically, nor your exchanges with your human coach. If you appreciate Noom&rsquo;s psychological coaching and daily lessons, many users keep using Noom for behavioral work and support groups, while using Lean daily for the TDEE calculation and precise tracking. The HealthKit \/ Google Health Connect sync, on the other hand, takes over immediately for your steps and activity history.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Download Lean and start the BodyScan AI right now. Free sign-up.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; What Lean unlocks<\/span><\/div>\n  <h2 id=\"deblock-h\">What Lean does, that Noom doesn&rsquo;t (on TDEE)<\/h2>\n  <p>Six features absent from consumer trackers. They all rest on the same choice: measuring every component of TDEE rather than estimating it, then dressing it up with teaching.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Unlimited BodyScan AI<\/div><p class=\"fd\">Your body fat percentage, obtained from a photo and updated every week. It is the variable that makes the metabolism individual, and no coaching program measures it.<\/p><\/div><div class=\"fc\">Body fat<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Unlimited AI photo scan of a meal<\/div><p class=\"fd\">A restaurant meal logged in two seconds, with no scale and no typing. The friction removed that makes you last twelve months, without needing a coach to chase you.<\/p><\/div><div class=\"fc\">Adherence<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Automatic metabolic adaptation<\/div><p class=\"fd\">Your TDEE corrects itself week after week according to the published ranges. The plateaus that a program blames on motivation find their numerical explanation here.<\/p><\/div><div class=\"fc\">Adaptation<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Live TDEE breakdown<\/div><p class=\"fd\">BMR, NEAT, EAT and TEF displayed separately and updated during the day. Your target moves with your real activity, instead of being fixed when you wake up.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Full history and trends<\/div><p class=\"fd\">Your weight, body fat and lean mass trends over several months. You identify your cycles instead of reacting to the day's weigh-in.<\/p><\/div><div class=\"fc\">History<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 unified tracking methods<\/div><p class=\"fd\">A clear hierarchy of what matters: adherence first, then calorie target, then steps. Enough to know what to adjust when things stall.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">You install the app for free, you test without commitment, then you decide whether the tool fits your goal.<\/p>\n<\/section>\n\n<section aria-labelledby=\"faq-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">11 &middot; FAQ<\/span><\/div>\n  <h2 id=\"faq-h\">Frequently asked questions<\/h2>\n  <div class=\"faq\">\n    <details><summary>Noom is known for its psychological coaching, why compare it to Lean on TDEE&nbsp;?<\/summary><div class=\"ans\">Noom is renowned for its behavioral approach (daily CBT-inspired lessons, human coaches, green\/yellow\/red food classification). That&rsquo;s a real strength for adherence and psychological work on eating. But the underlying calorie engine remains Mifflin-St Jeor 1990 without bodyfat, plus a static activity factor chosen through the sign-up quiz. On TDEE, the engine is basic. Lean recalculates your BMR every day on your real bodyfat measured by BodyScan AI, and modulates through metabolic adaptation. The two apps don&rsquo;t play on the same field.<\/div><\/details>\n    <details><summary>Why doesn&rsquo;t Noom calculate the BMR on real bodyfat&nbsp;?<\/summary><div class=\"ans\">Noom applies Mifflin-St Jeor 1990 by default without a lean-mass option. No bodyfat measurement is built into the app, and no Katch-McArdle-type equation is offered even in advanced settings. The consequence is mechanical: two users of the same weight but with 22 and 38 percent bodyfat get the same Noom BMR, while their real expenditure can differ by 400 kcal per day. Lean integrates BodyScan AI to measure your bodyfat from a simple photo, to redo every week.<\/div><\/details>\n    <details><summary>Is Noom&rsquo;s green\/yellow\/red classification a real metabolic measure&nbsp;?<\/summary><div class=\"ans\">No. The green\/yellow\/red system classifies foods by calorie density (vegetables in green, starches in yellow, fats and sugars in red). It&rsquo;s an educational behavioral tool, not a measurement of energy expenditure. It&rsquo;s effective for raising awareness about choices, but it doesn&rsquo;t influence the TDEE calculation. On your real metabolism, Noom stays on Mifflin 1990 plus a few static activity boxes. The color classification doesn&rsquo;t modify the calculated calorie target.<\/div><\/details>\n    <details><summary>Noom imports steps via HealthKit, is that enough for NEAT&nbsp;?<\/summary><div class=\"ans\">Noom imports steps and activity through Apple Health and Google Fit, but uses them to estimate an exercise expenditure added to the daily calorie target. The static activity factor picked at the sign-up quiz remains the base of the TDEE calculation. Lean, on the contrary, calculates NEAT directly from real steps measured every day, with no coefficient to pick.<\/div><\/details>\n    <details><summary>Does Noom&rsquo;s human coaching replace a precise TDEE calculation&nbsp;?<\/summary><div class=\"ans\">Noom&rsquo;s human coaching is a real added value for adherence and psychological work on habits. Chin 2016 and many meta-analyses show that behavioral therapy improves weight loss at 6 and 12 months. But coaching doesn&rsquo;t act on the underlying TDEE equation. If your calorie target is calculated on Mifflin 1990 without bodyfat and a static PAL, your coach won&rsquo;t fix the equation, he&rsquo;ll encourage you to hold a potentially wrong deficit. Coaching is an adherence multiplier, not a substitute for objective measurement.<\/div><\/details>\n    <details><summary>Can you use Lean and Noom in parallel&nbsp;?<\/summary><div class=\"ans\">Yes, it&rsquo;s defensible. If you appreciate Noom&rsquo;s human coaching, daily lessons, and behavioral pedagogy, you can keep Noom for the psychological and habits side. Lean takes care of the precise metabolic engine (BMR on real bodyfat, NEAT, EAT, TEF, adaptation). The databases are different (USDA + OpenFoodFacts on the Lean side, proprietary database on the Noom side) so the double-entry effort is real: it&rsquo;s a trade-off to arbitrate based on your priorities.<\/div><\/details>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"conclu\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">12 &middot; Conclusion<\/span><\/div>\n  <h2 id=\"conclu\">Coaching versus measurement<\/h2>\n  <p>It&rsquo;s not Noom versus Lean in marketing. It&rsquo;s psychological coaching versus metabolic precision, two different promises.<\/p>\n  <p>Noom remains one of the best mainstream apps for behavioral work on eating, and nobody in the mainstream does better on daily food-psychology lessons and human-coach accompaniment. But for your TDEE, Noom uses Mifflin-St Jeor 1990 without bodyfat measured inside the app, plus a frozen activity factor you tick once during the sign-up quiz, and ignores metabolic adaptation. The combination of all three makes any precise calorie tracking impossible beyond a few weeks of cut. It&rsquo;s mathematics. No human coach corrects an equation he doesn&rsquo;t see.<\/p>\n  <p>Lean was built to do the exact opposite: BMR based on <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/depense-energetique-totale-v2\/\">real bodyfat<\/a> (measured by BodyScan AI) via a proprietary patented model, <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-depense-non-sportive\/\">NEAT from real steps<\/a>, EAT per sport via MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/effet-thermique-des-aliments\/\">TEF from macros<\/a>, plus metabolic adaptation that modulates the BMR week after week. Each component calculated precisely, no magic coefficient, no psychological wrapping.<\/p>\n  <p>Noom remains very solid on behavioral coaching and human accompaniment. The best results often come from combining the two: measuring right (Lean) AND acting with discipline (sometimes helped by a Noom coach). If you tried Noom seriously and didn&rsquo;t get the results you hoped for on your cut, the problem isn&rsquo;t you, nor Noom on its psychological promise. The problem is the TDEE frozen under the hood. Change the engine, keep the coach alongside if you need it.<\/p>\n<\/section>\n\n<div class=\"get-band rev\">\n  <div class=\"kicker\">Download<\/div>\n  <h3>Lean is available as a free download<\/h3>\n  <p>iOS and Android. The BodyScan AI works from a single photo. No skinfold calliper, no bioimpedance scale, no DEXA.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download Lean on the App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download Lean on Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Further reading<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Internal links<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">Free online TDEE calculator<\/a> &middot; web version, no sign-up, same logic as the app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/depense-energetique-totale-v2\/\">Understand TDEE in depth (BMR, NEAT, EAT, TEF, adaptation)<\/a> &middot; deep-science article.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">How to count your calories properly<\/a> &middot; practical guide for beginners.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-depense-non-sportive\/\">NEAT: expenditure from steps and non-exercise activity<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/effet-thermique-des-aliments\/\">TEF: digestion burns calories<\/a>.<\/li>\n  <\/ul>\n<\/section>\n\n<section aria-labelledby=\"src\" class=\"sources\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Sources<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">References<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition.<\/li>\n    <li>Katch V.L., McArdle W.D. (1973). Prediction of body density from simple anthropometric measurements in college-age men and women. Human Biology.<\/li>\n    <li>Chin S.O. et al. (2016). Successful weight reduction and maintenance by using a smartphone application in those with overweight and obesity. Scientific Reports, behavioral therapy and weight loss.<\/li>\n    <li>Frankenfield D.C. et al. (2013). Validation of Mifflin-St Jeor equation in obese and non-obese populations. PubMed 23631843.<\/li>\n    <li>M&uuml;ller M.J., Bosy-Westphal A. (2015). Adaptive thermogenesis with weight loss in humans. Obesity, Minnesota revisit. PubMed 26399868.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n  <\/ol>\n<\/section>\n\n<\/main>\n\n<footer>\n  <div class=\"wrap\">\n    <div class=\"row\">\n      <div>\n        <div class=\"kicker\">Lean &middot; lean-app.com<\/div>\n        <p>Article published on May 24, 2026. Updated regularly with user feedback and relevant new studies. Lean is available on iOS and Android.<\/p>\n      <\/div>\n      <div class=\"stores\">\n        <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script>\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp',     drill:false},\n    kcal:     {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp',      drill:false},\n    depense:  {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp',   drill:true},\n    strategie:{src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp', drill:false}\n  };\n  var subMap = {\n    BMR:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp',\n    NEAT: 'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp',\n    EAT:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp',\n    TEF:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp'\n  };\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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-->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Read also<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"https:\/\/lean-app.com\/en\/metabolisme-de-base\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Basal Metabolic Rate (BMR): everything you need to know to calculate it accurately <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definition, TDEE equation, 4 historical formulas, why bodyfat changes everything.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/en\/depense-energetique-totale-v2\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Total Daily Energy Expenditure (TDEE): the canonical formula BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Understand the 4 components + metabolic adaptation, scientific sources 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/en\/comparatifs-croises\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">MyFitnessPal or Yazio? 12 calorie app head-to-heads compared <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Every verdict at a glance: who wins on what, and what neither of them calculates.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/en\/meilleures-applications-calories-2026\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Best calorie counting apps in 2026: 8 apps tested <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lean, MFP, Cronometer, Yazio, Lifesum, FatSecret, Noom, Foodvisor.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/en\/alternative-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Which MyFitnessPal alternative in 2026? 5 apps tested <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Honest comparison, TDEE accuracy, usability.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/en\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">All Lean comparisons against major calorie apps <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/en\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs MyFitnessPal: the TDEE formula that changes everything <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Why MFP gets your real calorie expenditure wrong.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/en\/lean-vs-foodvisor\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean versus Foodvisor: photo-scanning pioneer vs real expenditure <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Foodvisor sees your plate. Lean recomposes your TDEE continuously.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean TDEE Calculator Home &nbsp;\/&nbsp; Lean vs Noom Comparison &middot; Nutrition &amp; TDEE Lean vs Noom. Psychological coaching vs metabolic precision. Noom sells behavioral coaching to change your habits. Lean sees your real expenditure. Two promises that do not play on the same field. The Lean team &middot; Read 12&nbsp;min &middot; Updated [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1425","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs Noom: Coaching or Metabolic Accuracy? - Lean<\/title>\n<meta name=\"description\" content=\"Noom bets on behavioral coaching, Lean on exact expenditure calculation. 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